Apparatus and method to provide a recommedation of content

ABSTRACT

The invention relates to a recommender for recommending content to a user. The recommender comprises a recommender processor ( 111 ) which performs the steps of determining ( 201 ) a user preference profile and determining ( 205 ) if a content item interest does not correspond to the user preference profile. If the content item interest does not match the user preference profile, a temporary user preference profile is generated ( 207 ) in response to the content item. The recommender processor ( 111 ) then tests ( 209 ), through a user interface ( 107 ) the temporary user preference profile by recommending a plurality of other content items, and determining user preference values for them. If the preference value for the temporary user preference profile is high ( 211 ), the user preference profile is updated ( 213 ) accordingly. Otherwise, the temporary user preference profile is deleted ( 215 ). The update to the user preference profile may be temporary and have a higher update rate, thereby allowing the recommender to track temporary variations of user preferences. The recommender is particularly applicable to a Private Video Recorder ( 101 ).

FIELD OF THE INVENTION

The invention relates to a recommender and a method of providing arecommendation of content therefor and in particular to a recommendersuitable for a Private Video Recorder.

BACKGROUND OF THE INVENTION

In recent years, the accessibility to and provision of information andcontent such as TV programmes, film, music and books, etc. haveincreased explosively. The information and content may today be providedfrom many different sources, and the variety and availability of contenthas increased substantially.

For example, the number of available television channels in mostcountries has increased substantially in the last decade, and in manycountries, viewers can receive tens or even hundreds of different TVchannels. The TV channels are further provided from differentbroadcasters and sources and are communicated through a variety of mediaincluding terrestrial radio broadcasts, cable distribution or satellitebroadcasts. Similarly, the number of available radio channels hasincreased explosively and are provided through different media such assatellite broadcasts, digital terrestrial broadcasts, cable distributionor even through the Internet.

As the available content has increased substantially, it has becomeincreasingly difficult for a user to find and select the specificcontent that he is most interested in. Obtaining information of thetotal amount of content available and filtering this in order to selecta desired content item is a very time-consuming and cumbersome process.In addition to finding the appropriate content item, the user furtherneeds to determine from which source and at which time the desiredcontent item is available.

In order to facilitate content selection, and to filter the availablecontent to provide a suitable selection for a given user, recommendershave been developed, which are able to monitor the available content,and in response to a user profile, recommend content consideredspecifically suited for the user.

One area where recommenders have been implemented is in Private VideoRecorders (PVRs). A typical PVR comprises a hard disk for recordingcontent items such as TV programmes. The PVR further comprises arecommender, which records and recommends TV programmes to the user inaccordance with a user profile. The user profile is built up over timeto match the user's viewing habits, and the profile is specificallygenerated from specific user input related to the preference for a givenprogramme as well as from detecting which programmes are selected forviewing by the user of the PVR.

Although conventional recommenders may facilitate content selection andprovide recommendations, further improvement of the functionalityprovided would be advantageous.

For example, as the user profile is built up over a significant time, ittends to become relatively static, and modifications and updates canonly gradually be incorporated. Furthermore, the user profile isdetermined in response to the user's preference for selected programmes.However, as the user typically selects items recommended to him from thecontent, the update information available for the user profile istypically limited to content already recommended. Thus, the contentrecommendation will tend to become more and more narrow with onlycontent of a limited range being recommended. This further inhibitsdynamic changes and thus results in a static and narrow recommendationbeing provided to the user.

Hence, a system for an improved recommender would be advantageous, andespecially a system providing increased flexibility and/or dynamicperformance would be beneficial.

OBJECT AND SUMMARY OF THE INVENTION

Accordingly, the invention seeks to provide an improved system for arecommender and/or to mitigate, alleviate or eliminate one or more ofthe above-mentioned disadvantages singly or in any combination.

According to a first aspect of the invention, a method of providing arecommendation of content to a user comprises the steps of: determininga user preference profile; detecting a content item interest;determining if the content item interest does not correspond to the userpreference profile; and if so determining a temporary user preferenceprofile in response to the content item interest; determining if othercontent items associated with the temporary user preference profileachieve high user preference values and only if so, modifying the userpreference profile in response to the temporary user profile.

A user preference profile may thus be updated from a temporary userpreference profile. The temporary preference profile may be used to testcontent items not directly matching the user's current preferenceprofile, thereby allowing an increased flexibility and possibility ofimproved dynamic performance. Specifically, the temporary userpreference profile may allow alternative and/or additional preferencesto be tested, and if suitable to be added to the user preferenceprofile. Thus, a widening mechanism may be introduced to the userpreference profile, thereby opposing the narrowing effect caused by alimited recommendation of content for preference evaluation. The contentitems may be, for example, TV programmes, video clips, audio clips,radio programmes, music clips, multimedia clips or any other suitablecontent items. The content item interest may be determined in responseto a user behaviour such as a behaviour related to a selection ofcontent items.

According to a feature of the invention, a number of preference contentitems associated with the temporary user profile are recommended to theuser. Specifically, the suitability of the temporary user profile to theuser may be tested by recommending more content items that match thetemporary user preference profile. The other content items may thusspecifically be content items suggested by the recommender in accordancewith the temporary user preference profile. If these content itemsreceive a high user preference, the probability that the user preferenceprofile is updated in response to the temporary user preference profileis increased. The feature thus allows a reliable, easily implementableand easy to use method of testing the suitability of the temporary userpreference profile.

According to another feature of the invention, the step of determiningif the other content items achieve a high user preference valuecomprises determining a selection rate of the preference content items.The recommender may specifically determine how often a content itemmatching the temporary user preference profile is selected, and theselection of the content item may be considered to be a positivepreference indication by the user. The selection rate may specificallybe determined from how often a matching content item is selected, and/ormay be determined in response to how long the content item is selected.Thus, characteristics such as how quickly after selection the userselects another content item may be used in the determination of a userpreference. This provides an efficient method for determining a userpreference.

According to another feature of the invention, the number of preferencecontent items recommended before deciding whether to modify the userpreference profile depends on the selection rate. In particular, thetime before a decision is made whether to modify the user preferenceprofile or to delete the temporary user preference profile may depend onthe selection rate. Thus, if content items matching the temporary userpreference profile are frequently selected, the user preference profilemay be updated after relatively few selections. Furthermore, ifrecommended content items matching the temporary user preference profileare never selected, the temporary user preference profile may be deletedrelatively quickly. This allows a dynamic behaviour well suited to thespecific temporary user preference profile.

According to another feature of the invention, the step of determiningif the other content items achieve a high user preference valuecomprises determining a user rating of at least some of the preferencecontent items. This allows a simple to implement, yet very accurate userpreference determination.

According to another feature of the invention, the number of preferencecontent items recommended before deciding whether to modify the userpreference profile depends on the user rating of at least some of thepreference content items. Hence, the dynamic behaviour of themodifications to the user preference profile is adapted in response tothe probability of the temporary user preference profile being suitedfor the user.

According to another feature of the invention, the method furthercomprises the step of modifying the temporary user preference profile inresponse to the user preference values of the other content items.Hence, this provides for the option of the user directly affecting thetemporary user preference profile such that this may be updated andmodified to more accurately reflect a user profile for contentpreferences.

According to another feature of the invention, the modification of theuser preference profile is realized by including a user preferenceprofile addition. Specifically, the user preference profile may simplybe modified by the temporary user preference profile being added to thecurrent user preference profile. For example, the user preferenceprofile may simply add any preferences for content item categoriesdetermined in the temporary user preference profile to the preferencesstored in the user preference profile. This provides a simple method ofexpanding the preferences stored in the user preference profile and thusopposes the inherent narrowing effect of the recommender.

According to another feature of the invention, the user preferenceprofile addition is temporary. Specifically, the modification of theuser preference profile may not be permanent but may have a limitedduration only. This will allow the user preference profile to adapt totemporary preferences, for example, associated with a temporaryavailability of a specific category of content. Hence, an improveddynamic performance of the recommender may be achieved.

According to another feature of the invention, a dynamic updatecharacteristic of the user preference profile addition is different froma dynamic update characteristic of the user preference profile.Specifically, the user preference profile may thus comprise differentelements having a different dynamic performance. This may allow somepreferences to be quickly modified or updated in accordance with acurrent preference while preserving the accuracy of the long-termpreferences. Hence, an overall improved dynamic behaviour may beachieved without sacrificing long-term accuracy.

According to another feature of the invention, the content item interestis detected from a detection of a user selection of a content item. Thisprovides a suitable mechanism for detecting a content item interest.

According to another feature of the invention, the method furthercomprises the step of recommending the content item for initialselection. Specifically, the temporary user preference profile may begenerated from the recommendation and selection of a content item, whichdoes not match the determined user preference profile. This allows therecommender to test non-matching content items, thereby allowing awidening of the content item preferences so that the user preferenceprofile may be updated to include new preferences.

According to another feature of the invention, the recommendation of thecontent item is in response to an increase of preference values of otherusers for content items associated with the content item. This allowsthe preference of other users to be used as an indication that a givencontent item or category of content items may be applicable to thecurrent user. Hence, it allows the recommender to test if a new popularcontent item or category of content items will be suitable for the user.

According to another feature of the invention, the method furthercomprises the step of receiving topic interest information from anexternal source. Furthermore, the content item interest is detected inresponse to the topic interest information. This provides a suitableinput for suggesting content item that may be suitable for the user.

According to another feature of the invention, the external sourcecomprises at least one source chosen from the group of: newspapers;websites; and broadcast sources. These sources provide suitable andadvantageous sources for generating and distributing topic interestinformation.

According to a different aspect of the invention, there is provided arecommender for providing a recommendation of content to a user, therecommender comprising: a recommender processor for determining a userpreference profile; a user interface controller for detecting a contentitem interest; wherein the recommender processor is operable todetermine if the content item interest does not correspond to the userpreference profile; and if so to determine a temporary user preferenceprofile in response to the selected content item; and determine if othercontent items associated with the temporary user preference profileachieve high user preference values and only if so, modifying the userpreference profile in response to the temporary user preference profile.

BRIEF DESCRIPTION OF THE DRAWINGS

An embodiment of the invention will be described, by way of exampleonly, with reference to the drawings, in which

FIG. 1 is an illustration of a private video recorder comprising arecommender in accordance with an embodiment of the invention; and

FIG. 2 is an illustration of a method of providing a recommendation ofcontent in accordance with an embodiment of the invention.

DESCRIPTION OF PREFERRED EMBODIMENTS

The following description focuses on an embodiment of the inventionapplicable to a Private Video Recorder (PVR) comprising a recommender.However, it will be apparent that the invention is not limited to thisapplication but may be applied to many other applications includingrecommenders for radio programme content or Internet content.

For clarity and brevity, the description focuses on an embodimentwherein the content item interest is determined in response to a userselection of a content item.

FIG. 1 is an illustration of a private video recorder (PVR) 101comprising a recommender in accordance with an embodiment of theinvention. The PVR 101 comprises a content receiver 103. The contentreceiver 103 receives content items from one or more suitable contentitem sources. In the preferred embodiment, the content receiver 103mainly receives content by way of TV programmes broadcast in a suitableway.

However, in the preferred embodiment, the content receiver is furthercapable of receiving content from a plurality of various contentsources. Thus, the content receiver receives content items in the formof video, audio and multimedia clips and programmes. Specifically, TVprogrammes are received from terrestrial radio broadcasts as well asfrom a digital cable connection. Likewise, radio programmes are receivedfrom conventional analogue radio transmissions as well as from digitalradio broadcasts received through a cable connection. The contentreceiver capable of receiving a plurality of content items from varioussources may simply be implemented as the combination of a plurality ofindependent content receiver elements, where each element is dedicatedto receiving content items of a specific nature from a specific source.

The received content items are converted to suitable digital formats andstored in a content memory 105 together with information associated withthe content items. Specifically, a content item may be received directlyin a suitable format, such as an MPEG 2 format for a video transmission,and in this case no conversion is required.

The PVR 101 further comprises a user interface 107 for displayingcontent items, control information and for receiving user input.Specifically, the user interface 107 comprises a display such as e.g. avideo monitor or a TV. In the preferred embodiment, the user input isreceived by using a remote control communicating with the user interface107. Hence, the user interface is operable to display variousinformation to the user and to receive user input. Specifically, theuser interface may display a list of content items, and a user mayselect one of these through a suitable activation of the remote control.

The PVR additionally comprises a content presenter 109, which is coupledto the content memory 105 and the user interface 107. In response to aselection of a content item, the content presenter 109 is operable toretrieve the stored content from the content memory 105 and present itto the user via the user interface 107.

Furthermore, the PVR 101 comprises a recommender processor 111 coupledto the content receiver 103, the content presenter 109, the userinterface 107 and possibly the content memory 105. The recommenderprocessor 111 is operable to generate a user preference profile for auser of the PVR 101.

In the preferred embodiment, the recommender processor 111 detects whichcontent items are presented by the content presenter 109. It furthermoredetermines a user preference for the content items through a specificuser preference indication received through the user interface 107.Additionally or alternatively, the user preference indication may bereceived through indirect measures. These indirect measures includedetection of, for example, how many times a given content item iswatched, whether it is watched in full or only partly etc.

When the recommender processor 111 detects that a given content item ispresented to the user, it retrieves the associated information from thecontent memory 105. The user preference is correlated with theinformation for the content item, and specifically with the category ofthe content item, in order to derive information of the user'spreference for this category of content item. In this way, therecommender processor 111 builds up knowledge of the user's preferencesfor different categories and types of content. This knowledge iscontained in a user preference profile, and the PVR 101 comprises a userpreference profile memory 113 for storing the user preference profile.The user preference profile memory 113 is coupled to the recommenderprocessor 111.

In the preferred embodiment, the PVR 101 is further operable todetermine a temporary user preference profile. This temporary userpreference profile may be stored in a temporary user preference profilememory 115 coupled to the recommender processor 111.

FIG. 2 is an illustration of a method of providing a recommendation ofcontent in accordance with an embodiment of the invention. The methodmay be applicable to the PVR of FIG. 1, and will hereinafter bedescribed with reference thereto.

In step 201, a user preference profile is determined. In the preferredembodiment, the user preference profile is determined in response toprevious user selections. Hence, specifically a user preference profileis generated when the PVR 101 is first initiated and is then stored inthe user preference profile memory 113. The user preference profile iscontinually updated as the PVR is used, and becomes increasinglyaccurate and specific as more and more information is determined. Thedetermination of the user preference profile of step 201 may comprisethe process of generating a new user preference profile. However, in thepreferred embodiment, the determination of step 201 comprises therecommender processor 111 determining the user preference profile simplyby accessing the information stored in the user preference profilememory 113. Hence, the determination preferably simply consists inretrieving or accessing some or all information of the user preferenceprofile stored in the user preference profile memory 113.

In step 203, it is determined if a new content item has been selected.The step is repeated until a positive detection of a selection occurs.In the preferred embodiment, step 203 is furthermore associated with oneor more content items being recommended to the user. Specifically, thesecontent items may comprise a number of content items that match theuser's preference profile but will in addition comprise some contentitems that do not provide a close match to the user's preferenceprofile. These “surprise” suggestions allow content items to berecommended to the user that do not match the current user preferenceprofile, and therefore may be used to modify and update the userpreference profile to include new preferences.

When a new content item has been selected, the method continues in step205 wherein it is detected if the selected content corresponds to theuser preference profile and specifically in the preferred embodiment,whether it matches the user's current user preference profile. If theselected content item does match the user preference profile, thecontent presenter 109 proceeds to present the content item to the userand the method returns to step 203.

If the selected content item does not match the user preference profile,the method continues in step 207 wherein a temporary user preferenceprofile is determined in response to the selected content item. Thus, anew temporary user preference profile is generated, which in thepreferred embodiment is initialised with a positive preference value forthe one or more of categories to which the content item belongs. Thus,if a user who is not normally interested in sport, and therefore has alow preference value for sport in the user preference profile, selects acontent item consisting in a TV programme of, for example, a footballmatch at the Olympic Games, the temporary user preference profile may bestarted with a positive preference value for the categories of Sport,Football and the Olympic Games.

The method continues in step 209 wherein further information is gatheredfrom other content items to further determine the user preference valuesfor the temporary user preference profile. Specifically, in thepreferred embodiment, the temporary user preference profile is tested bya number of other content items belonging to the categories of thetemporary user preference profile. The user preference values for theseother content items are determined and used to determine how suitablethe temporary user preference profile is for the user. In addition, thetemporary user preference profile is preferably updated and modified inaccordance with the determined preference values.

As a specific example, following the selection of the Olympic footballmatch, the recommender processor 111 may recommend, through the userinterface 107, a number of sports programmes including, for example,another Olympic football match, a domestic football match and an OlympicAthletics event such as a 100 m sprint. User preference values aredetermined for these recommendations, and specifically a positive valueis associated with the content items that are selected, whereas anegative value is associated with content items that are not selected.

Hence, if the user selects none of the recommended clips, a low overallpreference value is achieved by the temporary user preference profile.If all of the recommended clips are selected, a high overall preferencevalue is achieved by the temporary user preference profile. If only someof the clips are selected, the temporary user preference profile isupdated accordingly in the preferred embodiment. Hence, if the userselects content items related to two other Olympic events, the temporaryuser preference profile is changed to reflect a high preference for theOlympic category but a lower preference for the category of footballmatches. In this way, the temporary user preference profile is furthermodified to more accurately reflect the new preference of the user.

In the preferred embodiment, many other approaches for determining apreference value are used in addition to the method described above.Specifically, the user interface 107 may receive explicit preferenceindications from the user and communicate these to the recommenderprocessor 111, which will modify and update the temporary userpreference profile accordingly. Additionally or alternatively, otheruser behaviour may be used as information for determining the preferencevalues including determining how quickly a user moves on to anothercontent item, whether he samples topics from other sources by selectingthese sources for short durations and how long the user selects a givencontent item.

Hence, in the preferred embodiment, the temporary user preferenceprofile is further refined and tested in step 209 by recommending anumber of preference content items associated with the temporary userprofile.

Step 209 is followed by step 211 wherein it is determined if thetemporary user preference profile has achieved high user preferencevalues. If high preference values are achieved, the method continues instep 213 by modifying the user preference profile in response to thetemporary user profile. If high preference values are not achieved, themethod continues in step 215 by deleting the user preference profile.

In the preferred embodiment, the duration and/or number of other contentitems recommended or selected before a decision is made on whether todelete the temporary user preference profile or to update the userpreference profile depends on the preference values obtained.Specifically, the number of preference content items recommended beforedeciding whether to modify the user preference profile depends on theselection rate or a user rating of at least some of the preferencecontent items. Hence, if most of the content items recommended inaccordance with the temporary user preference profile are selected, andare given high user ratings, the user preference profile is modifiedvery soon. However, if none or only a few of the content itemsrecommended in accordance with the temporary user preference profile areselected, and these are given low user ratings, the user preferenceprofile will soon be deleted. In contrast, if the results are lessconclusive, for example, because a relatively high number of othercontent items are selected but these are given low user ratings, thetest duration is extended and more content items matching the temporaryuser preference profile are recommended in order to further test thetemporary user preference profile.

In the preferred embodiment, the modification of the user preferenceprofile is by including a user preference profile addition. Thus theoriginal user preference profile is augmented by including of theinformation from the temporary user preference profile. Specifically,the user preference profile may be modified by the categories of thetemporary user preference profile having high preference values beingadded to the user preference profile. Thus, in the specific example, ifthe temporary user preference profile indicates that the content itemcategory relating to the Olympic Games has a high preference value, thiscategory is added to the user preference profile.

In some embodiments, the user preference profile addition may betemporary. Thus the temporary user preference profile is not necessarilyintegrated with the user preference profile but may be a separableaddendum that can be deleted at a later date. Hence, this allows atemporary interest or preference to be taken into account and used bythe recommender without causing a lasting change to the user preferenceprofile. For example, the user preference profile may be updated by theincluding of a high preference for content item related to the OlympicGames. However, when the Olympic Games finish, this category may bedeleted.

In the preferred embodiment, a dynamic update characteristic of the userpreference profile addition is different from a dynamic updatecharacteristic of the user preference profile. Thus, in this embodiment,the update rate and modification rate for the user preference profile istypically significantly slower than for the user preference profileaddition. Therefore, it will require a more significant and substantialchange of behaviour to modify the user preference profile, whereas theuser preference profile addition will be updated and modified by muchfewer preference value inputs. For example, the user preference profilemay have been built up over years of monitoring user behaviour, and willtherefore very accurately reflect the user's average preferences. Inorder to retain this information and accuracy, very significantpreference values for a high number of content items are required for asubstantial change to be made to the user preference profile. However,the user preference profile addition may have been based on only a fewdays or weeks information, and therefore reflect current deviations fromthe average preferences of the user. In order to follow the variationsof the user's preferences, much fewer content items are required forsignificant changes to be made to the user preference profile addition.

In the specific example, a user may not be interested in sports ingeneral but be interested in following current Olympic Games. Thedescribed embodiment will allow the exception to the average lowpreference for sport to be detected, and will result in a temporary userpreference profile and consequent user preference profile addition.Hence, within perhaps a few days, the recommender will have detected andupdated the recommendations to include content items related to theOlympic Games. When the Olympic Games finish, no content items in thiscategory will be selected, and due to the high update rate of the userpreference profile addition, the preference value for sports events isquickly returned to the normal levels. Hence, the short-term preferencevariations may be tracked without impact on the long-term averagepreference profile.

It will be appreciated that any content item interest not closelymatching the user preference profile may be used to initiate thetemporary user preference profile in the preferred embodiment. However,preferably a recommendation of one or more content items is made inresponse to an increase of preference values of other users for contentitems associated with these content items. Hence, the behaviour of otherusers is preferably used to recommend content items to the user whichmay result in a temporary user preference profile. Specifically,currently popular content items and categories of content items may bedetermined and detected and used to provide recommendations to the user.For example, it may be detected that there is a general increase inselection and preference values for sports events and that thesespecifically relate to recently begun Olympic Games. In response,content items related to the Olympic Games may initially be recommendedto the user, and if selected, a temporary user preference profile may beinitiated in response.

It will be apparent that some communication of information related tothe behaviour of other users is required. This may be provided in anysuitable way and specifically it may be included as data in the receivedbroadcast transmissions. Likewise, any suitable method for detecting thebehaviour and preference values of different users may be used. In someembodiments, a number of PVRs may be connected to a centralcommunication unit, which receives and processes selection informationin order to generate the information of the behaviour of a plurality ofusers.

Additionally or alternatively, the recommender may receive informationrelated to content item interests from an external source. For example,the recommender may directly receive information of topics that aregenerally of interest to many users. This information may be direct suchas information specifically generated for the purpose by a central unit.The user of the PVR may thus have a subscription entitling him toreceive information related to content items, including topic interestinformation indicating e.g. issues or events of current high generalinterest. In other embodiments, the topic interest information may bemore indirect and may be derived by the recommender from indirectinformation. This may include information from e.g. newspapers where theheadlines can be analysed to provide indications of topics of currenthigh general interest. Alternatively or additionally, one or morewebsites may be accessed and analysed for indications of high interesttopics. In some embodiments, topic interest information may be comprisedin or derived from a broadcast. Specifically, the information may beincluded as data embedded in the content item broadcast signals.

The invention can be implemented in any suitable form includinghardware, software, firmware or any combination of them. However, theinvention is preferably implemented as computer software running on oneor more data processors and/or digital signal processors. The elementsand components of an embodiment of the invention may be physically,functionally and logically implemented in any suitable way. Indeed, thefunctionality may be implemented in a single unit, in a plurality ofunits or as part of other functional units. As such, the invention maybe implemented in a single unit or may be physically and functionallydistributed between different units and processors.

Although the present invention has been described in connection with thepreferred embodiment, it is not intended to be limited to the specificform set forth herein. Rather, the scope of the present invention islimited only by the accompanying claims.

1. A method of providing a recommendation of content to a user themethod comprising the steps of: determining (201) a user preferenceprofile; detecting (203) a content item interest; determining (205) ifthe content item interest does not correspond to the user preferenceprofile; and if so determining (207) a temporary user preference profilein response to the content item interest; determining (209) if othercontent items associated with the temporary user preference profileachieve high user preference values and only if so, modifying (213) theuser preference profile in response to the temporary user preferenceprofile.
 2. A method as claimed in claim 1, wherein a number ofpreference content items associated with the temporary user profile arerecommended to the user.
 3. A method as claimed in claim 2, wherein thestep of determining (209) if the other content items achieve a high userpreference value comprises determining a selection rate of thepreference content items.
 4. A method as claimed in claim 3, wherein thenumber of preference content items recommended before deciding whetherto modify the user preference profile depends on the selection rate. 5.A method as claimed in claim 2, wherein the step of determining (209) ifthe other content items achieve a high user preference value comprisesdetermining a user rating of at least some of the preference contentitems.
 6. A method as claimed in claim 5, wherein the number ofpreference content items recommended before deciding whether to modifythe user preference profile depends on the user rating of at least someof the preference content items.
 7. A method as claimed in claim 1,further comprising the step of modifying the temporary user preferenceprofile in response to the user preference values of the other contentitems
 8. A method as claimed in claim 1, wherein the modification (213)of the user preference profile is realized by including a userpreference profile addition.
 9. A method as claimed in claim 8, whereinthe user preference profile addition is temporary.
 10. A method asclaimed in claim 8, wherein a dynamic update characteristic of the userpreference profile addition is different from a dynamic updatecharacteristic of the user preference profile.
 11. A method as claimedin claim 1, wherein the content item interest is detected from adetection of a user selection of a content item.
 12. A method as claimedin claim 11, further comprising the step of recommending the contentitem for initial selection.
 13. A method as claimed in claim 12, whereinthe recommendation of the content item is in response to an increase ofpreference values of other users for content items associated with thecontent item.
 14. A method as claimed in claim 1, further comprising thestep of receiving topic interest information from an external source andwherein the content item interest is detected in response to the topicinterest information.
 15. A method as claimed in claim 13, wherein theexternal source comprises at least one source chosen from the group of:a. newspapers; b. websites; and c. broadcast sources.
 16. A computerprogram enabling a method to be carried out according to claim
 1. 17. Arecommender for providing a recommendation of content to a user, therecommender comprising: a recommender processor (111) for determining auser preference profile; a user interface controller (107) for detectinga content item interest; wherein the recommender processor (111) isoperable to determine if the content item interest does not correspondto the user preference profile; and if so, to determine a temporary userpreference profile in response to the selected content item; anddetermine if other content items associated with the temporary userpreference profile achieve high user preference values and only if so,modifying the user preference profile in response to the temporary userpreference profile.
 18. A private video recorder (101) comprising arecommender as claimed in claim 17.